Collateral Ventilation Quantification Using Xenon-Enhanced Dynamic Dual-Energy CT: Differences between Canine and Swine Models of Bronchial Occlusion
Korean Journal of Radiology
;
: 648-656, 2015.
Article
in English
| WPRIM
| ID: wpr-83659
ABSTRACT
OBJECTIVE:
The aim of this study was to evaluate whether the difference in the degree of collateral ventilation between canine and swine models of bronchial obstruction could be detected by using xenon-enhanced dynamic dual-energy CT. MATERIALS ANDMETHODS:
Eight mongrel dogs and six pigs underwent dynamic dual-energy scanning of 64-slice dual-source CT at 12-second interval for 2-minute wash-in period (60% xenon) and at 24-second interval for 3-minute wash-out period with segmental bronchus occluded. Ventilation parameters of magnitude (A value), maximal slope, velocity (K value), and time-to-peak (TTP) enhancement were calculated from dynamic xenon maps using exponential function of Kety model.RESULTS:
A larger difference in A value between parenchyma was observed in pigs than in dogs (absolute difference, -33.0 +/- 5.0 Hounsfield units [HU] vs. -2.8 +/- 7.1 HU, p = 0.001; normalized percentage difference, -79.8 +/- 1.8% vs. -5.4 +/- 16.4%, p = 0.0007). Mean maximal slopes in both periods in the occluded parenchyma only decreased in pigs (all p < 0.05). K values of both periods were not different (p = 0.892) in dogs. However, a significant (p = 0.027) difference was found in pigs in the wash-in period. TTP was delayed in the occluded parenchyma in pigs (p = 0.013) but not in dogs (p = 0.892).CONCLUSION:
Xenon-ventilation CT allows the quantification of collateral ventilation and detection of differences between canine and swine models of bronchial obstruction.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Respiration
/
Swine
/
Xenon
/
Bronchial Diseases
/
Bronchography
/
Pulmonary Ventilation
/
Tomography, Spiral Computed
/
Airway Obstruction
/
Disease Models, Animal
Limits:
Animals
Language:
English
Journal:
Korean Journal of Radiology
Year:
2015
Type:
Article
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